Optimal transformation of LSP parameters using neural network

Hai Le Vu, Laszlo Lois

Research output: Contribution to journalConference articleOther

6 Citations (Scopus)

Abstract

In this paper, the intraframe correlation properties of Line Spectrum Pair (LSP) are used to develop an efficient encoding algorithm using the Karhunen-Loeve (KL) transformation. An important nonuniform statistical characteristics of LSP frequencies are investigated. Based upon this nonuniform property the neural network based techniques for generating the transform vectors via system training are studied. Using Principal Component Analysis (PCA) network to decorrelate LSP coefficients, we show that these new approaches lead to as good or better distortion as compared to other methods for speech analysis-synthesis.

Original languageEnglish
Pages (from-to)1339-1342
Number of pages4
JournalICASSP Proceedings
Volume2
Publication statusPublished - 1 Jan 1997
Externally publishedYes
EventProceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 5) - Munich, Ger
Duration: 21 Apr 199724 Apr 1997

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